The perception of dialect variation by naïve listeners is a
growing research area in the field of sociolinguistics. Dialect
geographers and variationist sociolinguists have been documenting regional
and social linguistic varieties of American English for more than a
century (McDavid, 1958) and the implications of
variation for social interactions have been explored by social
psychologists for several decades (Ryan & Giles,
1982). More recently, experimental methods from speech science have
been applied to the study of linguistic variation to uncover the
perceptual categories that naïve listeners have for regional and
social dialects (Thomas, 2002). While the goal
of most of these studies was to understand how naïve listeners
perceive linguistic variation and/or make judgments about the regional
and social background of unfamiliar talkers, many recent studies have also
explored the role of the listeners' background in the perception of
dialect variation. In particular, a listener's residential history,
including region of origin, geographic mobility, and travel experience,
have been found to play an important role in shaping the perception of
linguistic variation.
In one of the earliest studies of dialect categorization, Preston
(1993) asked naïve adults in Michigan and
Indiana to listen to a set of nine male talkers and then select the city
that they thought each talker was from. The talkers came from nine
different cities along a north-south continuum in the United States
between Saginaw, Michigan, and Dothan, Alabama. The listeners heard a
short extract from an interview with each of the talkers and were then
asked to select from the nine cities the one that they thought the talker
was from. Preston (1993) found that while the
naïve listeners could make reliable distinctions between Northern and
Southern talkers, their ability to distinguish between Northern and
Midland talkers was more limited.
In addition, he found that the geographic boundary between the North
and the South was different for the two groups of listeners. In
particular, the southern Indiana listeners perceived the talker from their
own region as more similar to the Northern talkers than the Michigan
listeners did. Preston (2002) attributed this
difference in perception to differences in “linguistic
security” in the two regions.1
Linguistic security is defined with respect to the
participants' ratings of the “correctness” of their
speech and the speech of others. Linguistically secure participants rate
their own speech as highly correct. Linguistically insecure participants
rate their own speech as less correct than some other varieties that are
perceived to be the standard or norm (Preston,
1993).
In particular, Michigan listeners are typically
found to be linguistically secure, whereas listeners in southern Indiana
are typically less linguistically secure (Preston,
1993,
2002). Preston (
2002) argued that this difference in perceived
prestige of their own variety led to the use of different identification
strategies in the categorization task for the two groups of listeners. In
particular, the southern Indiana listeners used cues to perceived
“pleasantness” in making their categorization judgments,
whereas the listeners from Michigan relied on cues to perceived
“correctness.”
In the United Kingdom, Williams, Garrett, and Coupland (1999) recorded narratives in English from two
adolescent male talkers from each of six different regions of Wales, plus
two adolescent male speakers of Received Pronunciation (RP). They played
30-second extracts of these narratives to a different group of adolescent
males in Wales and asked them to select the region that they thought each
talker was from using an eight-alternative forced-choice categorization
task (the response categories were the six regions of Wales, RP, and
“don't know”). The authors found that the listeners
performed the task with overall accuracy of approximately 30%. Williams et
al. (1999) also observed several effects of
residential history and linguistic experience on performance in their
categorization task. First, although the performance of the adolescent
boys was 30% correct overall, a more detailed examination of the results
revealed that the listeners were far more accurate in the categorization
of talkers from their own region (45%) than of talkers from other regions
(24%). Second, Williams et al. (1999) also asked
schoolteachers in Wales to participate in the dialect categorization task
and found that the adults were more accurate than the children, with
overall accuracy of 52% across all of the talkers for the adults, compared
to 30% overall accuracy for the children. Williams et al. (1999) attributed this difference in categorization
performance between the children and the adults to the greater travel
experiences of the adults as compared to the children.
More recently, Clopper and Pisoni (2004b)
played sentence-length utterances read by male talkers from six different
dialect regions in the United States to naïve listeners. The stimulus
materials were taken from the TIMIT Acoustic-Phonetic Continuous Speech
Corpus, which contains recordings of 630 talkers (Fisher, Doddington, & Goudie-Marshall, 1986). The
talkers in the TIMIT corpus include both males and females with a range of
ages, ethnicities, and regional backgrounds. The six dialect regions
examined by Clopper and Pisoni (2004b) were New
England, North, North Midland, South Midland, South, and West. We found
that naïve listeners were 31% accurate in categorizing unfamiliar
talkers by dialect. While this performance was poor overall, it was
statistically above chance in a six-alternative task. Clopper, Conrey, and
Pisoni (2005) replicated the earlier results
reported by Clopper and Pisoni (2004b) for a
group of female talkers and a mixed group of both male and female
talkers.
Clopper and Pisoni (2004b) also analyzed the
pattern of perceptual errors produced in the categorization task and found
that the listeners made systematic confusions between phonologically
similar dialects. In particular, the listeners appeared to make consistent
distinctions between Northeastern, Southern, and Western varieties of
American English, but were far less accurate in identifying the six
regional subvarieties within each of these larger clusters. We also found
evidence of perceptual similarity differences due to residential history.
In a post hoc analysis, we divided the listeners into three groups by
region of origin: Northern Indiana, Southern Indiana, and Out-of-State.
The clustering analysis revealed significant differences between the
listener groups. In particular, the Southern Indiana listeners (from the
South Midland dialect region) perceived a greater difference between the
Southern and South Midland talkers than the other two listener groups.
These results suggest that the listeners' region of origin may affect
their perception of local varieties and allow for greater discrimination
between local dialects.
Clopper and Pisoni (2004a) explicitly
examined the effects of residential history on dialect categorization
performance using the same six-alternative forced-choice task described
earlier. Two groups of participants were recruited who differed in their
residential history with respect to geographic mobility. One group, the
“mobile” listeners, had lived in at least three different
states in the United States. The second group, the “nonmobile”
listeners, had lived only in Indiana. We found that the mobile group
performed slightly better than the nonmobile group, but this difference
was only significant for one of the three blocks of trials. A more
detailed analysis of the performance by the mobile listeners with respect
to which dialect regions they had lived in revealed more interesting
results. In particular, listeners who had lived in a given region
(“residents”) performed more accurately on talkers from that
same region than listeners who had not lived there
(“nonresidents”). This result was robust across all of the
dialect regions. Finally, an analysis of the perceptual similarity of the
dialects for these listeners revealed that the mobile listeners tended to
perceive greater differences between neighboring regions such as the North
and North Midland or South and South Midland than the nonmobile listeners
did. Taken together, the findings from these perceptual dialect
categorization studies suggest that geographic location and mobility
affect naïve listeners' perceptual categories. In particular,
listeners are more accurate and can better distinguish between local
varieties as opposed to nonlocal varieties. In addition, mobile listeners
tend to be more accurate overall and show greater discrimination between
contiguous dialect regions.
Several studies have also reported that linguistic experience and
residential history can affect listeners' perception of vowel
categories and their ability to perceptually adapt to the dialect of an
unfamiliar talker. In one early study, Willis (1972) asked listeners in Buffalo, New York, and Fort
Erie, Ontario, to categorize synthetic vowel stimuli using an open-set
response format. On each trial, the listeners heard a single synthetic
vowel and were asked to write down an English word containing that vowel.
Willis (1972) found significant differences in
the perceptual boundaries between
and between
for the two listener groups. First, the Fort Erie listeners distinguished
between
based on first formant (F1) frequencies, whereas the Buffalo listeners
did not clearly discriminate these two categories with respect to either
F1 or second formant (F2) frequencies. Second, the Buffalo listeners
perceived the boundary between
at a higher second formant frequency than the Fort Erie listeners. Both
of these differences in perception reflect differences in production
between these two cities: the speech of the Buffalo area is characterized
by the Northern Cities Chain Shift, including the raising of
and the fronting of
,
whereas the speech of the Fort Erie area is characterized by the Canadian
vowel shift, which does not involve a shift in either of these two
vowels.
Labov and Ash (1997) reported the results of
two experiments designed to explore the role of dialect familiarity on the
perception of vowel quality. In the first experiment, listeners in
Philadelphia, Chicago, and Birmingham were asked to identify the vowel in
kVd (e.g., kid, ked, cad) words produced by a
native Birmingham talker. The Birmingham listeners showed a general
advantage over the nonlocal listeners in identifying the vowels,
particularly for the most shifted vowels such as
,
although the advantage was relatively small in most cases. The small, but
consistent, local advantage was replicated in the second experiment in
which listeners from the three cities were presented with words, phrases,
and sentences extracted from Birmingham interview speech and were asked to
identify the target word. Taken together, the results of the experiments
by Willis (1972) and Labov and Ash (1997) suggest that residential history, particularly
region of origin, affects the perception of vowel quality in both
synthetic and naturally produced speech.
More recently, Rakerd and Plichta (2003)
examined the perception of the Northern Cities Chain Shift by listeners
from Detroit, Michigan, and the Michigan Upper Peninsula. The listeners
were asked to identify a series of synthetic stimulus items as
sock or sack. The stimuli varied in their second formant
frequency and were presented to the listeners both in isolation and at the
end of carrier sentences produced by a Detroit talker and an Upper
Peninsula talker. The Detroit talker produced the shifted vowels found in
the Northern dialect region, whereas the Upper Peninsula talker did not.
Rakerd and Plichta (2003) found that the Detroit
listeners, who were exposed to the Northern Cities Chain Shift in their
local variety, were able to adapt to the dialect of the talker producing
the carrier sentence and selected sock for more stimuli with
higher second formant frequencies for the Detroit carrier sentence than
for the Upper Peninsula carrier sentence or the words in isolation.
However, the listeners from the Upper Peninsula, who were not as familiar
with the characteristic vowel productions of the Northern Cities Chain
Shift, appeared to use the same second formant frequency cutoff for
distinguishing sock from sack, regardless of the
context.
In a similar study in Great Britain, Evans and Iverson (2004) asked listeners in Northern and Southern Britain
to rate synthetic stimuli embedded in carrier sentences on their goodness
as exemplars of Northern or Southern British English. They found that
listeners from Northern England with little exposure to Southern varieties
showed less dialect-specific variation in their responses and tended to
select Northern variants regardless of the target dialect. In contrast,
listeners from Northern England who had moved to Southern England showed
greater adaptation to the dialect in the carrier sentence and selected
more accurate variants for the Southern British vowels. The studies by
Evans and Iverson (2004) and Rakerd and Plichta
(2003) suggest that prior linguistic experience
can affect the perception of the phonological properties that distinguish
different dialects.
Finally, one early study also revealed a relationship between
residential history and cross-dialect intelligibility. Mason (1946) reported the results of a speech intelligibility
experiment in noise in which the talkers and listeners came from different
regions of the United States. He found that performance was better when
the talkers and listeners shared a dialect than when the talkers and
listeners were from different dialect regions. These speech
intelligibility findings suggest that residential history affects the
perception of the linguistic content of the message, in addition to the
perception of isolated vowels or the regional background of the
talker.
Taken together, the results of these studies suggest that experience
with language variation affects performance on explicit tests of dialect
categorization and identification, as well as vowel identification and
speech intelligibility tasks. In particular, Preston (1993), Williams et al. (1999), Clopper and Pisoni (2004b), Willis (1972), Labov
and Ash (1997), Rakerd and Plichta (2003), and Mason (1946) all
found that geographic location affected perception. In addition, Clopper
and Pisoni (2004a), Evans and Iverson (2004), and Williams et al. (1999) found that exposure to different varieties
through travel or geographic mobility also led to differences in
perception. In general, geographic mobility leads to greater overall
accuracy in explicit categorization and identification tasks, whereas the
location of the listeners interacts with the dialect of the talkers and
leads to more accurate categorization responses when the talkers and
listeners have the same regional dialect than when they do not.
The present study was designed to extend the previous research in
several ways. First, dialect categorization performance was assessed using
a six-alternative forced-choice categorization task that was similar to
the experimental methods used in our earlier studies (Clopper et al., 2005; Clopper & Pisoni, 2004a, 2004b), except that
the stimulus materials were taken from the new Nationwide Speech Project
corpus (Clopper, 2004). The stimulus materials
used by Clopper and Pisoni (2004a, 2004b) were taken from the TIMIT corpus, which was
originally designed for use in speech recognition research (Fisher et al., 1986). As a result, the sociolinguistic
properties of the corpus were not well controlled. The original regional
labels used to describe the dialects of the talkers were questionable,
both in terms of their names and the geographic regions that they covered,
and it is unclear what demographic criteria were used to determine which
region a given talker should be assigned to. We therefore expected to
confirm the reliability of our previous research through a replication of
the accuracy and perceptual similarity results with a new set of stimulus
materials that are more sociolinguistically motivated. The results will
provide additional evidence for naïve listeners' perception of
three primary dialects of American English: Northeast, South, and
West.
Second, the geographic location and mobility of the listeners were
experimentally manipulated to create four listener groups: (1) Mobile
Northerners; (2) Mobile Midlanders; (3) Non-Mobile Northerners; and (4)
Non-Mobile Midlanders. Previous research has typically explored either
mobility or location (but not both) or has relied on post hoc analyses of
the effects of residential history on perception. By explicitly
manipulating two variables of residential history in the current study, we
were able to explore the contributions of these two sources of listener
differences, independently and together, to the explicit categorization of
regional dialects.
Finally, the data obtained from this task were analyzed with respect
to overall accuracy, perceptual similarity, and response biases. Based on
the previous research, we expected that the mobile listeners would be more
accurate overall than the non-mobile listeners due to their greater
experience with dialect variation in the United States and that all of the
listeners would show a benefit for local talkers (either Midland or
North). We expected the perceptual similarity analysis to reveal that the
error patterns of all four listener groups reflected the broad
organization of American English varieties into Northern, Southern, and
Western groups. We predicted that the perceptual similarity spaces for the
mobile listeners would show greater overall distances between neighboring
dialects than the similarity spaces for the non-mobile listeners. In
addition, we predicted that location would affect the perception of
neighboring regions, such as North versus New England or Midland versus
South. Previous research has not examined the role of response bias in
dialect perception, but we expected to uncover further evidence of the
role of experience in categorization behavior. In particular, we predicted
that the listeners would show negative biases towards less familiar
regions, such as the West or New England, and positive biases towards
local, more familiar, regions, such as the North or Midland. Taken
together, the results of this experiment will provide converging evidence
with previous studies of the role of linguistic experience and dialect
familiarity on the explicit identification of the regional background of
unfamiliar talkers.
METHODS
Listeners
One hundred and fifteen listeners aged 18–25 years old were
recruited from the Indiana University community for participation in this
study. Data from 16 participants were excluded prior to the data analysis
for the following reasons: three performed the task consistently at
chance,2
Participants who did not correctly
categorize at least five tokens from one of the six dialects were
identified as performing consistently at chance and their data were
excluded. It is impossible to determine if these participants were unable
to perform the task accurately or if they were simply not attending to the
task, but this strict exclusion criteria ensures that the data analyzed
reflect the best efforts of the participants.
nine knew one or
more of the talkers by name, one was fluent in a language other than
English, and three reported a history of a hearing or speech disorder at
the time of testing. The remaining 99 listeners were all monolingual
native speakers of American English with native English-speaking parents
and no reported hearing or speech disorders. The participants received $8
for their services.
The 99 listeners who participated in the present study were assigned
to one of four groups, based on their residential history. The 25
listeners in the Non-Mobile Midland group had lived only in the Midland
dialect region.3
The Northern and Midland
dialect regions were geographically identical to those used in the
Nationwide Speech Project corpus (Clopper,
2004). Specifically, highway US-30 served as the primary divide
between the Northern and Midland regions in Ohio, Indiana, and Illinois.
The southern boundary of the Midland dialect ran along the southern border
of Ohio, Indiana, and Illinois, with the three Indiana counties
neighboring Louisville, Kentucky, included in the Southern
region.
The 25 listeners in the Non-Mobile North group had lived
only in the Northern dialect region, prior to attending college in
Bloomington, Indiana, and their parents still lived in the Northern
dialect region at the time of testing. The 25 listeners in the Mobile
Midland group had lived in at least one dialect region other than the
Midland before the age of 18 years old and their parents lived in the
Midland dialect region at the time of testing. The 24 listeners in the
Mobile North group had lived in at least one dialect region other than the
North before the age of 18 years old and their parents lived in the
Northern dialect region at the time of testing. The four groups of
listeners therefore represented two levels of geographic mobility (mobile
and non-mobile) and two levels of geographic location (North and Midland)
as shown in
Table 1.
Residential history of the 99 listeners in the six-alternative
forced-choice categorization experiment
Most of the 49 mobile listeners had lived in only one other dialect
region in the United States (N = 37). Of the remaining 12 mobile
listeners, eight had lived in two other dialect regions and four had lived
in three or more other dialect regions. In addition, two of the mobile
listeners had also lived abroad. The dialect regions represented included
New England (N = 5), Mid-Atlantic (N = 9), North
(N = 9, Mobile Midland group only), Midland (N = 8,
Mobile North group only), South (N = 11), West (N = 9),
Western Pennsylvania (N = 4), and the Florida peninsula
(N = 6). Thus, even though the data were collected at a large
Midwestern university, the mobile listeners were quite variable in their
experiences and only 17 of the mobile listeners (35%) had lived in both
the Northern and Midland dialect regions. The amount of time spent in
other regions was also quite variable across participants. Some of the
mobile listeners had lived outside their home region for as little as one
year, while others had moved into their home region for the first time
during high school.
Talkers
The talkers for the current study were selected from the Nationwide
Speech Project (NSP) corpus (Clopper, 2004),
which includes recordings of five males and five females from each of six
dialect regions in the United States: New England, Mid-Atlantic, North,
Midland, South, and West. Each talker was recorded producing a range of
utterances, including isolated words, sentences, and conversational
speech. The talkers are all white, native speakers of American English
with native English-speaking parents. Each talker was a non-mobile
resident of his or her dialect region with both parents also raised in the
same region. The talkers ranged in age from 18 to 25 years old and were
all recorded within two years of moving to Bloomington, Indiana, to reduce
the effects of dialect leveling.
The talkers in the NSP corpus were unevenly distributed geographically
within each of the six dialect regions. Most of the Mid-Atlantic talkers
were from New York City and New Jersey, most of the Northern talkers were
from Northern Illinois and Indiana, most of the Midland talkers were from
central Indiana, half of the Southern talkers were from Kentucky, and half
of the Western talkers were from Southern California. However, the New
England region was represented by talkers from both Eastern and Western
New England.
Four males and four females from each of the six regions were selected
for the current study, for a total of 48 different talkers. The hometowns
of these 48 talkers are shown in Figure 1. The
dark circles indicate male talkers and the light squares indicate female
talkers. Forty-eight of the 60 talkers included in the NSP corpus were
selected for the present study to allow for two complete blocks of novel
sentence trials. By reducing the number of talkers to 48, two stimulus
items could be presented for each talker without repeating any of the
sentences during the course of the experiment. The four talkers of each
gender from each dialect were selected randomly.
Map showing the hometowns of the 48 talkers in the six-alternative
forced-choice categorization task. Dark circles indicate male talkers and
light squares indicate female talkers.
The six dialect regions represented by the talkers in the NSP corpus
differ with respect to their vowel systems. The Northern dialect is
characterized by the Northern Cities Chain Shift which involves the
clockwise rotation of the low and low-mid vowels, beginning with the
raising and fronting of
(Labov, 1998). The Southern dialect is
characterized by the Southern Vowel Shift, which involves the fronting of
the high and mid back vowels, the centralization of the front tense
vowels, and the peripheralization of the front lax vowels (Labov, 1998). Southern speech also contains
monophthongal
(Thomas, 2001). The Mid-Atlantic dialect
includes raising of
and a split in words containing
such that some exhibit raising and some do not (Labov,
1994; Thomas, 2001). The New England,
Midland, and Western dialects all exhibit the low-back merger of
to some degree (Labov, 1998). Western New
England speech also includes some aspects of the Northern Cities Chain
Shift (Boberg, 2001). Midland speech exhibits
some /u/ and /o/ fronting (Labov, Ash,
& Boberg, 2005). Finally, Western speech is also characterized
by the fronting of /u/ (Labov et al.,
2005; Thomas, 2001).
Clopper, Pisoni, and de Jong (2005) analyzed
the vowel systems of the talkers included in the NSP corpus and found
evidence of the Northern Cities Chain Shift among the Northern talkers and
the Southern Vowel Shift among the Southern talkers. In particular, the
Northern talkers reliably produced raised and fronted
and lowered and fronted
,
as well as variably backed
.
The Southern talkers produced reliably fronted /u/s and
centralized /e/s and variably peripheralized
.
The New England, Midland, and Western talkers exhibited the low-back
merger and variable /u/ fronting. In addition, the Midland talkers
exhibited variable
peripheralization, /e/ centralization, and
raising. The New England talkers also produced variable
raising. Finally, the Mid-Atlantic talkers produced backed
and fronted
.
The talkers included in the current study thus produced regionally-marked
vowel variants that naïve listeners should be able to use in
identifying the regional background of the talkers based on short samples
of speech.
Stimulus materials
Two different meaningful English sentences were selected for each of
the 48 talkers, for a total of 96 different stimulus items. The sentences
were taken from the Speech Perception in Noise (SPIN) test and ranged in
length from five to eight words (Kalikow, Stevens,
& Elliott, 1977). The sentences were selected for each talker
such that no sentence was repeated over the course of the experiment. In
addition, the sentences were selected to highlight regional variation by
selecting sentences that contained shifted vowels. For example, the
sentences produced by the Northern talkers typically included raised
or fronted
.
Sentences produced by the Southern talkers, on the other hand, included
fronted /u/ or monophthongal
.
A complete list of stimulus sentences is shown in the Appendix.
The original digital sound files from the NSP corpus were edited to
include only speech material and converted for auditory presentation to
the listeners to .wav digital sound files with 16-bit encoding and a
sampling rate of 44.1 kHz. The mean RMS amplitude level of each of the
sound files was leveled to 67 dB using Level 16 (Tice
& Carrell, 1998).
Procedure
The experiment consisted of two blocks of 48 trials each. In each
block, participants heard one sentence from each of the 48 talkers one at
a time in random order. For each talker, each of the two sentences was
assigned randomly to either the first or second block for each listener to
reduce stimulus-specific block effects. Two blocks of trials were used to
increase the total number of data points obtained from each listener and
therefore provide additional statistical power for the analyses. If the
listeners performed similarly across the two blocks of trials, we would
also have evidence that the task itself produced stable, reliable results
across different stimulus materials, particularly given that the materials
themselves were randomly assigned to the first or second block for each
individual listener.
Participants were seated at personal computers equipped with a mouse
and Beyerdynamic DT100 headphones. On each trial, the participants heard a
single sentence over the headphones at approximately 70 dB SPL (sound
pressure level) and were asked to select the region that they thought the
talker was from. The response alternatives were displayed on a CRT display
using a multicolored map of the United States with a verbal label assigned
to each of the six regions, as shown in Figure
2. Before making their responses, the listeners were permitted to
listen to each sentence as many times as they wanted by pressing a
“Listen Again” button with the mouse. The listeners recorded
their responses by clicking on the appropriate label on the screen with
the mouse. The experiment was self-paced and the listeners pressed a
“Next Trial” button to proceed to the next trial. No feedback
was provided to the listeners about the accuracy of their responses.
Participants were permitted to take a break between the two blocks of
trials.
Response alternatives in the six-alternative forced-choice
categorization task.
RESULTS
Four analyses of the results of the perceptual dialect categorization
experiment were conducted. First, we examined overall categorization
accuracy to determine how well the listeners were able to identify the
regional background of the talkers based on short samples of speech and to
explore the role of residential history in categorization accuracy. Based
on previous research (Clopper & Pisoni,
2004a; Williams et al., 1999), we
expected the listeners to perform poorly, but statistically above chance,
and that the mobile listeners would be more accurate overall than the
non-mobile listeners. Second, we analyzed the number of stimulus
repetitions to examine the effects of residential history on repeated
listening to the stimulus materials. We predicted that the non-mobile
listeners might require more stimulus repetitions before making their
responses if they found the task more difficult due to lower overall
familiarity with the different regional dialects. Third, given that we
expected the listeners to make a large number of errors, we also conducted
an analysis of the listeners' error patterns using perceptual
similarity scaling techniques, including a clustering analysis, to explore
their perceptual responses in more detail. We expected this analysis to
reveal that the error patterns produced by the listeners were
systematically related to the phonological properties of the dialects, and
that the listener groups would exhibit different perceptual similarity
structures as a result of their different residential histories. This
analysis allowed us to compare the perception of dialect variation by
naïve listeners to the descriptions of phonological variation in the
United States reported by trained sociolinguists. Finally, we examined the
response biases of the listeners to explore the extent to which response
biases may have affected overall performance and the perceptual similarity
structures obtained in the third set of analyses. Specifically, the
analyses of the response biases could help explain differences between the
perception of dialect variation by naïve and trained listeners.
Categorization accuracy
A summary of the perceptual categorization performance for each of the
four listener groups is shown in the middle column of Table 2. Chance performance in a six-alternative task
is 17%. While the overall accuracy of the listeners was low, all four
groups were statistically above chance by a binomial test (all p
< .05).
Overall mean percent correct performance and mean number of stimulus
repetitions in the six-alternative forced-choice categorization task for
each listener group, collapsed across experimental block and talker
dialect
A repeated measures analysis of variance (ANOVA) with experimental
block (first or second) and talker dialect (New England, Mid-Atlantic,
North, Midland, South, or West) as within-subject variables and listener
group (Mobile North, Mobile Midland, Non-Mobile North, or Non-Mobile
Midland) as a between-subject variable revealed a significant main effect
of talker dialect (F(5,475) = 43.2, p < .001) and a
significant experimental block × talker dialect interaction
(F(5,475) = 2.8, p = .015). No other main effects or
interactions were significant.
Figure 3 shows the percent correct
performance across all four listener groups for each of the two
experimental blocks for each of the six dialects. Post hoc Tukey tests on
talker dialect for each experimental block revealed the locus of the
interaction as well as the overall main effect of dialect. For the first
block of trials, performance on the New England talkers was worse than
performance on any of the other talker groups (all p < .05).
Performance on the Midland talkers was the best, with significant
differences in performance revealed between the Midland talkers and all
other groups except the South (all p < .05). Significant
differences were also found between Mid-Atlantic and Western talkers
(p < .001), Northern and Southern talkers (p <
.001), and Southern and Western talkers (p < .001). Similarly,
for the second block of trials, performance on the New England and Western
talkers was significantly worse than performance on the other four talker
groups (all p < .05). Performance on the Midland talkers was
also best in the second block, with significant differences found between
Midland talkers and all of the talker groups except the South (all
p < .01).
Percent correct categorization for each of the six talker dialect
groups in each of the two experimental blocks, collapsed across listener
group. Error bars indicate standard error.
The locus of the block × dialect interaction reflects the
improvement in performance on New England and Northern talkers in the
second block relative to the first. Paired sample t tests
confirmed a significant improvement in performance on New England and
Northern talkers from the first to the second experimental block
(t(98) = −2.3, p < .05 for New England and
t(98) = −3.0, p < .01 for North). No
significant differences in performance between the first and second
experimental blocks were found for the other four talker dialect
groups.
Table 3 shows the performance of each of the
four listener groups on each of the six talker dialects. As confirmed by
the repeated measures ANOVA, performance was highly consistent across the
four listener groups with respect to talker dialect.
Percent correct categorization performance for each listener group for
each talker dialect, collapsed across experimental block
Overall, performance was best for Midland and Southern talkers and
worst for New England and Western talkers, with performance on
Mid-Atlantic and Northern talkers in between. Performance on the New
England and Northern talkers improved from the first block to the second
block. Recall that the stimulus materials were assigned to the first or
second block randomly for each listener so that the same set of materials
were not presented in the first and second block for every listener.
Therefore, this effect is most likely due to experience with the task
itself and with the range of variation in the stimuli and not to
stimulus-specific differences. Finally, we did not find any evidence of
effects of residential history on overall categorization accuracy.
Stimulus repetitions
The mean number of stimulus repetitions for each of the listener
groups, collapsed across experimental block, is shown in the last column
of Table 2. A repeated measures ANOVA on
stimulus repetitions with experimental block (first or second) as a
within-subject variable and listener group (Mobile North, Mobile Midland,
Non-Mobile North, or Non-Mobile Midland) as a between-subject variable
revealed a significant main effect of experimental block (F(1,95)
= 6.6, p = .012). The listeners repeated the stimulus items more
often in the first block of trials (M = 1.74) than in the second
block of trials (M = 1.65). Neither the main effect of listener
group nor the block × listener group interaction were significant.
Thus, across all four listener groups and both experimental blocks, the
participants chose to listen to the stimulus items an average of 1.69
times before making their response and they repeated fewer stimuli as the
experiment progressed from the first block to the second block of trials.
Given that the experiment lasted approximately 10 minutes, it is unlikely
that this effect is a result of participant fatigue and more likely
reflects the listeners' adaptation to the task and the range of
variability present in the stimulus materials.
Perceptual similarity
Previous research on dialect categorization performance has shown that
residential history can affect the perceptual similarity space of dialect
categories for naïve listeners (Clopper & Pisoni, 2004a, 2004b). Therefore, in
addition to examining the listeners' performance in terms of overall
categorization accuracy, we also explored the patterns of errors produced
by each of the four listener groups. This perceptual similarity analysis
involved two phases. First, similarity and bias parameters were extracted
from the raw categorization confusion data using Luce's (1963) and Shepard's (1957) Similarity Choice Model (SCM). Second, the
resulting similarity parameters were submitted to an additive clustering
analysis (Corter, 1982; Sattath & Tversky, 1977) to produce a graphical
model of the perceptual similarity of the six regional dialects.
For each listener group, a 6 × 6 stimulus-response confusion
matrix was calculated based on the listeners' responses in the
six-alternative forced-choice task. The confusion matrices were summed
over the two experimental blocks and the stimulus items were grouped by
dialect. The four listener group confusion matrices were submitted to the
full Similarity Choice Model (Luce, 1963; Shepard, 1957) to determine similarity and bias
parameters. The similarity parameters indicate the degree of similarity
between each pair of dialects. Similarity is assumed to be symmetric, so
that the similarity between two categories i and j is
equivalent to the similarity between j and i. The bias
parameters provide an index of the response biases of the listeners and
are discussed in more detail in the next section. Taken together, the
similarity and bias parameters can be used to produce a model of
perceptual categorization data that reveals the underlying perceptual
similarity space of a set of objects or concepts (Nosofsky, 1985; Smith,
1980). In the current experiment, the objects were the six dialect
regions: New England, Mid-Atlantic, North, Midland, South, and West.
A restricted version of the SCM analysis was also conducted in which
the similarity parameters were held constant across all four listener
groups, while the bias parameters were free to vary. If the restricted
model produced results that did not fit the original data significantly
worse than the full model, in which the similarity parameters were also
free to vary across listener groups, then we would have evidence that the
structure of the perceptual similarity spaces of the regional dialects of
American English was equivalent for the four listener groups. In fact,
however, the restricted SCM analysis produced a significantly worse fit to
the data than the full model. The listener groups therefore differed in
their perceptual similarity spaces of dialect variation.
To assess the effects of the independent variables of mobility and
geographic location on perceptual similarity, we also compared the
perceptual similarity spaces of pairs of listener groups, using the
restricted SCM. Significant differences were found in similarity structure
between the Mobile North and Mobile Midland groups, the Mobile North and
Non-Mobile North groups, and the Non-Mobile North and Non-Mobile Midland
groups. However, the Non-Mobile Midland and Mobile Midland groups were not
significantly different (Gtest2 = 6.0,
df = 15, χcrit2 = 7.3, p >
.05). Thus, the perceptual similarity spaces of the two Midland listener
groups were equivalent, whereas the two Northern listener groups differed
from each other and from their Midland counterparts.
The similarity parameters that were obtained from the SCM analyses
were submitted to ADDTREE, an additive clustering scheme that produces
graphical representations of perceptual similarity in tree form (Corter, 1982). For the Mobile North and Non-Mobile
North groups, the similarity parameters from the full SCM analyses were
used. For the Midland groups, the similarity parameters from the
restricted model were used and a single tree representation was produced,
because the restricted SCM analysis revealed equivalent perceptual
similarity spaces across the two Midland listener groups.
The results of the ADDTREE analysis are shown in Figure 4. In these representations, perceptual
similarity is inversely related to vertical distance. That is, the
perceptual dissimilarity of any two dialect regions is represented by the
sum of the lengths of the least number of vertical branches required to
connect them. Horizontal distances are irrelevant in the interpretation of
the figures. For example, the perceptual “distance” between
New England and Mid-Atlantic for the Mobile Northern listeners is the sum
of the length of the short branch labeled “New England” and
the length of the longer branch labeled “Mid-Atlantic.”
However, the perceptual distance between the South and the Midland for the
Mobile Northerners is the sum of the long branch labeled
“South,” the long branch labeled “Midland,” and
the short branch connected to the West/Midland node. With respect to
interpreting the clusters, objects that share a node lower in the tree
(such as New England and Mid-Atlantic in the Mobile North figure) are
perceptually “closer” than objects that share a higher-level
node (such as New England and North in the Mobile North figure).
Clustering solutions for the Mobile North, Non-Mobile North, and
Midland listeners.
Inspection of Figure 4 reveals a general
pattern of perceptual similarity across all three listener groups (Mobile
North, Non-Mobile North, and Midland). First, in all three panels of Figure 4, Southern and Mid-Atlantic talkers are
farthest from the root, suggesting that they are perceptually the most
distinctive dialects of those examined in the current study. Second, the
New England and Mid-Atlantic talkers share a low-level node and therefore
cluster together perceptually for all three groups, although New England
(which is closer to the root) is always perceptually less distinct from
the other dialects than the Mid-Atlantic (which is farther from the root).
While the lengths of the New England and Mid-Atlantic branches differ, the
Mid-Atlantic and New England dialects share a node and are therefore
closer to each other perceptually than to any of the other dialects.
Finally, the Western and Midland talkers are also perceptually similar
across all three listener groups. Thus, all of the listener groups had
perceptual categories for Southern talkers, Northeastern (New England and
Mid-Atlantic) talkers, and Western (Midland and Western) talkers.
The perception of Northern talkers was affected by the residential
history of the listeners. In particular, while the structure of the trees
for the Midland and Mobile Northern listener groups are virtually
identical, the structure of the similarity model for the Non-Mobile
Northern group is different. Specifically, the Northern talkers are
relatively closely linked to the Mid-Atlantic and New England talkers in
the trees for the Midland and Mobile Northern listeners. For the
Non-Mobile Northern listeners, however, the Northern talkers are linked
more closely to the Midland talkers. These differences suggest that the
Non-Mobile Northern listeners perceived the Northern talkers as being more
similar to the Midland talkers than the other groups did. That is, the
listeners who had only lived in the Northern dialect region perceived
themselves as being quite similar to their Midland peers. On the other
hand, the listeners who had lived in the Midland dialect region for their
whole lives and the listeners who had lived in more than one dialect
region perceived the Northern talkers as being less similar to the Midland
talkers and more similar to the New England and Mid-Atlantic talkers.
The highly similar perceptual structures revealed by the ADDTREE
analysis for the Midland and Mobile Northern listener groups is striking.
However, a Similarity Choice Model analysis of the stimulus-response
confusion matrices restricting similarity parameters across the two
Midland listener groups (Mobile and Non-Mobile) and the Mobile North
listener group provided a significantly worse fit than the unrestricted
full model, suggesting significant underlying differences between the
Midland and Mobile Northern listeners. A closer inspection of the
similarity parameters produced by the SCM analyses and the tree models
produced in the ADDTREE analysis revealed that the Mobile Northern
listeners were better able to distinguish the Southern and Mid-Atlantic
talkers from the other talker dialect groups than the Midland listeners.
In Figure 4, this greater perceptual
distinctiveness is seen in the relatively longer lengths of the vertical
branches for the Northern, Midland, and Western talkers for the Mobile
Northern listeners than for the Midland listeners. This finding suggests
that although the Southern and Mid-Atlantic talkers were the most
distinctive across all three listener groups, this perceptual
distinctiveness was greater for the Mobile Northern listeners than for the
Midland listeners. This difference is also reflected in the somewhat
better (although not statistically significant) overall categorization
performance by the Mobile Northern listeners than the Midland listeners
(see Table 2).
Across the four listener groups, a common pattern of perceptual
similarity emerged in which the South and the Mid-Atlantic were the most
distinctive dialects. In addition, the New England talkers clustered with
the Mid-Atlantic talkers to create a perceptual Northeastern dialect. The
Midland and Western talkers also clustered together in a third salient
dialect. Thus, the results of this six-alternative forced-choice task
suggest that the three main perceptual dialects of American English for
naïve listeners from the Midland and Northern dialect regions are
Northeast, South, and Midwest/West. In addition, both the geographic
location and mobility of the listeners affected their perceptual
similarity structures. The Non-Mobile Northern listeners differed from
their Mobile Northern counterparts and their Non-Mobile Midland
counterparts, particularly with respect to the similarity of the Northern
and Midland talkers.
Response biases and asymmetries
The Similarity Choice Model analysis (Luce,
1963; Shepard, 1957) also produced
response bias parameters in addition to the similarity parameters used in
the additive clustering analysis. The bias parameters provide an
indication of the response biases of the listeners. In a forced-choice
categorization task in which each category is presented an equal number of
times in the stimulus materials, we would predict that the response biases
of the listeners would be roughly equivalent across all of the response
alternatives. In particular, with six categories, each response
alternative should be selected 1/6 or 17% of the time, if the
listeners were unbiased in their responses.
The observed response biases for the four groups of listeners are
shown in Table 4. The bias parameters for the
Northern listener groups (Mobile and Non-Mobile) are based on the full SCM
analysis. The bias parameters for the Midland listener groups (Mobile and
Non-Mobile) are based on the restricted model in which similarity
parameters were held constant across both groups, because the restricted
SCM analysis revealed equivalent similarity parameters for the two Midland
groups. An examination of the bias parameters in Table
4 reveals a tendency across all four listener groups to display a
positive bias towards Midland responses and a negative bias towards New
England responses. That is, the listeners responded “Midland”
more often and “New England” less often than if they were
theoretically unbiased in their responses. The bias parameters for the
other four talker groups are fairly close to the unbiased .17 response
rate, suggesting little response bias for those categories.
Bias parameters produced in the Similarity Choice Model analysis for
each of the four listener groups
One additional aspect of the participants' stimulus-response
patterns was captured by the Similarity Choice Model analysis:
asymmetrical response patterns. Asymmetrical patterns of similarity are
not uncommon in categorization or similarity ratings experiments. In one
classic example, participants will typically rate the similarity of North
Korea to China as being greater than the similarity of China to North
Korea, because China is perceived as being an appropriate baseline for
comparison whereas North Korea is not (Tversky,
1977). In the present study, the raw confusion data produced by the
naïve participants in the six-alternative forced-choice task suggest
that this type of perceptual asymmetry may also be present for the
categorization of regional varieties of American English.
Table 5 shows the stimulus-response
confusion matrix collapsed across all 99 listeners. Stimuli are presented
in the rows and responses in the columns. Thus, each cell reflects the
proportion of the total number of responses to a given stimulus category
that were from a given response category. One example of a perceptual
asymmetry that was uncovered by the SCM analysis is the strong negative
response bias for New England and the strong positive response bias for
Midland. Table 5 shows that the New England
talkers were categorized as North and Midland much more frequently than
the North and Midland talkers were categorized as New England. However, in
general, the New England response category was selected much less
frequently than either the North or Midland response category and the bias
parameters in Table 4 reflect this
asymmetry.
Proportion of responses from each of the six response alternatives to
each of the six stimulus categories in the six-alternative forced-choice
categorization task, collapsed across all 99 listeners
Another striking example of a perceptual asymmetry in similarity is
the difference in the proportion of Mid-Atlantic talkers categorized as
New England (.25) and the proportion of New England talkers categorized as
Mid-Atlantic (.15) (see Table 5). While the raw
probabilities are not too different, many more errors were made on the New
England talkers than the Mid-Atlantic talkers overall. Thus, 35% of the
incorrect responses to Mid-Atlantic talkers were New England responses,
whereas only 17% of the incorrect responses for the New England talkers
were Mid-Atlantic responses. The SCM and ADDTREE analyses revealed a high
degree of similarity between the New England and Mid-Atlantic regions,
however, masking this important perceptual asymmetry. The SCM analysis was
unable to model this particular perceptual asymmetry due to the overall
tendency for a low response bias for New England. Thus, while some of the
stimulus-response asymmetries were reflected in the similarity and bias
parameters produced in the SCM analyses, the fact that the Mid-Atlantic
talkers were more often confused with New England talkers than vice versa
was not captured by the model.
The analysis of the response biases revealed a positive bias for
“Midland” responses and a negative bias for “New
England” responses. The negative response bias for the New England
response category led to an asymmetry between New England, Midland, and
North responses, such that New England talkers were categorized as Midland
and North more often than Midland and Northern talkers were categorized as
New England. The New England response category was also involved in
another asymmetry with the Mid-Atlantic category. In particular, while the
New England response category was selected less often overall than the
other response alternatives, the Mid-Atlantic talkers were
disproportionately miscategorized as New Englanders. Taken together, these
results suggest that the listeners' overall level of familiarity with
the six dialects had a significant effect on their categorization
performance, particularly with respect to the Midland and New England
responses.
DISCUSSION
The results of the present study are consistent with previous research
on the perceptual categorization of dialect variation in the United States
and Europe with respect to overall categorization accuracy and perceptual
dialect similarity structures. However, some differences were observed
between the earlier research and the present experiment due to properties
of the stimulus materials and the task demands. The addition of the
response bias analysis also revealed novel findings about the role of
dialect familiarity in perceptual dialect categorization performance.
Finally, we observed significant effects of the listeners' geographic
location and mobility on perceptual dialect similarity.
Categorization accuracy
Overall performance as measured by accuracy was 26% correct, which is
low but statistically above chance. In addition, this level of performance
is a little lower than the 31% accuracy reported by Clopper and colleagues
for similar tasks with different stimulus materials (Clopper et al., 2005; Clopper & Pisoni, 2004a, 2004b). One important
difference between our earlier work and the results of the present study,
however, is the corpus from which the stimulus materials were obtained for
presentation to the listeners. The earlier research was conducted using
sentences obtained from the TIMIT Acoustic-Phonetic Continuous Speech
Corpus (Fisher et al., 1986). As discussed
earlier, the original design of the TIMIT corpus was not well controlled
with respect to regional linguistic variation in the United States. First,
the regional labels provided for each talker do not correspond to dialect
regions based on current sociolinguistic research (Labov et al., 2005). Second, the criteria that were
used to assign the regional label to each talker did not explicitly
control for the residential history of the talkers and their parents. The
speech samples used in the current study, however, were taken from the
Nationwide Speech Project corpus (Clopper,
2004), which was designed specifically for perceptual and acoustic
analyses of dialect variation in the United States. Therefore, the
sociolinguistic components of the corpus were more carefully controlled
and documented. The dialect labels and geographic regions included in each
dialect were based on current sociolinguistic research by Labov and his
colleagues (Labov et al., 2005). Details about
the residential history of the talkers and their parents were obtained
from each talker and only lifetime residents of each dialect region were
included in the corpus.
Based on the differences between the two corpora, we might expect that
performance would be better in the present study than in the previous
studies because the talkers more accurately reflected regional dialect
variation in the United States. One crucial difference, however, is the
inclusion of talkers from both New England and the Mid-Atlantic in the
current experiment. Although the TIMIT corpus contained talkers from New
York City, they were too few in number to be included in the previous
research (Clopper et al., 2005; Clopper &
Pisoni, 2004a, 2004b).
Therefore, performance in the current study may be lower overall because
the listeners were required to distinguish between New England and
Mid-Atlantic talkers. In addition, the New England talkers in the previous
experiments (Clopper & Pisoni 2004a, 2004b) were all r-less, whereas the talkers
in the current experiment were all r-ful, which may have reduced
the phonological salience of the New England talkers.
The results of the accuracy and response bias analyses both suggest
that this particular aspect of the categorization task was quite difficult
for the naïve listeners in this study. In particular, the listeners
were quite poor in accurately categorizing New England talkers. In
addition, they categorized Mid-Atlantic talkers as New Englanders about
25% of the time. Thus, the lower performance found in the present study
may be a better reflection of the dialect categorization abilities of
naïve listeners in the United States than the previous results
reported by Clopper and her colleagues (Clopper et al.,
2005; Clopper & Pisoni, 2004a, 2004b), which did not require the listeners to make
distinctions between the two Northeastern varieties of American English,
New England and Mid-Atlantic.
The difficulty of dialect categorization tasks in general may be
partly the result of individual talker differences, particularly as they
relate to regional dialect. For example, the Western dialect region is
geographically huge compared to the other five regions. Therefore,
intraregional variation might be partly responsible for the poorer
performance on the Western talkers. Intraregional variation is not
restricted to large areas such as the West, however, and Clopper et al.
(2005) found evidence of intertalker variation
among the New England and Midland talkers, as well.
Clopper and Pisoni (2004b) also reported
that dialect categorization performance was better for some talkers than
others, even within a single dialect, suggesting that individual talkers
may differ in the degree to which they exhibit dialect-specific properties
that are salient for naïve listeners. Some of the previous dialect
perception studies (e.g., Evans & Iverson,
2004; Rakerd & Plichta, 2003) have
attempted to eliminate talker-specific variation through the use of
synthetic stimulus materials. However, these studies are typically limited
to the perception of a single variant and do not provide listeners with
the range of vocalic, consonantal, and prosodic variation that occurs in
naturally produced speech. In addition, the use of naturally produced
intradialect, intertalker variability permits us to investigate the
perception of variation at multiple levels of specificity, including
within and across dialects, within and across gender, and within and
across individual talkers. However, the use of natural speech makes it
more difficult to isolate the precise linguistic variants that naïve
listeners attend to in making explicit dialect categorization judgments,
particularly when different sentence materials are used, as in the current
experiment. Further research using both natural and synthetic stimuli is
needed to explore the role of individual linguistic variants, and the
combinations of variants, that are salient for naïve listeners in
perceptual dialect categorization studies, as well as the role of
individual talker variability in the perception and representation of
dialect variation by naïve listeners.
Perceptual similarity
Despite the somewhat lower overall level of categorization
performance, the results of the perceptual similarity analyses are
consistent with previous research on the perceptual similarity of regional
varieties of American English (Clopper & Pisoni, 2004a, 2004b). As expected,
the clustering analysis revealed three primary perceptual dialect
clusters: Northeast, South, and Midwest/West. These three clusters are
quite similar to the perceptual clusters described by Clopper and
colleagues (Clopper et al., 2005; Clopper &
Pisoni, 2004a, 2004b)
based on our earlier research using sentences taken from the TIMIT
corpus.
The perceptual similarity spaces of the listeners were also consistent
with the phonological properties of the dialects, as discussed in the
sociolinguistics literature. For example, Labov (1998) described the three major dialects of American
English as North, South, and the “Third Dialect” (which
includes the West and the Midland), with the Mid-Atlantic as an exception.
Carver (1987) defined the major dialects as
North and South, with the Western region included in the North. Even as
early as 1925, Krapp divided the varieties of
American English into Eastern, Southern, and Western (or General) American
groups.
For the specific set of talkers used in the current study, significant
acoustic-phonetic differences were found for the Mid-Atlantic, Northern,
and Southern talkers, while the overall similarity between the New
England, Midland, and Western talkers was quite high (Clopper et al., 2005). Specifically, while the
Mid-Atlantic, Northern, and Southern talkers all exhibited significant
vowel shifts, the New England, Midland, and Western talkers were
characterized by the low-back merger and variable /u/ fronting
and
raising (New England and Midland only). Thus, the perceptual similarity
of the dialects reflects the overall phonological properties of the
talkers included in the NSP corpus.
The perceptual similarity of the Northern talkers with respect to the
other dialects was affected by the residential history of the listeners.
In particular, the Non-Mobile Northern listeners perceived the Northern
talkers as being most similar to the Midland talkers, whereas the Midland
and Mobile Northern listeners perceived the Northern talkers as being more
similar to the New England talkers. This result is of theoretical interest
for several reasons. First, it confirms that a listener's residential
history affects the perception of dialect variation, although the effect
is in the opposite direction than what was predicted. For the Northern
listeners, mobility was a contributing factor in the perceptual similarity
of the Northern and Midland dialects. At the same time, for the Non-Mobile
listeners, region of origin was relevant to perceptual similarity of these
same two dialects. However, the Northern listeners actually perceived
greater similarity between themselves and their Midland neighbors rather
than a greater difference.
However, the finding that the lifetime residents of the Northern
dialect region (the Non-Mobile Northern listener group) did not attend to
the difference between Northern and Midland talkers is consistent with an
earlier study by Niedzielski (1999) that
examined the perception of the Northern Cities Chain Shift. In her study,
Niedzielski (1999) asked listeners in Detroit,
Michigan, to match natural vowel stimuli to synthetically produced vowel
tokens based on vowel quality. The listeners were presented with
sentence-length utterances read by a female talker from the Detroit area
and were asked to pay attention to a target word in the sentence. They
were then presented with six synthetic vowel stimuli that included a range
of first and second formant frequencies and were asked to select the vowel
token that was the best match to the target. Prior to the beginning of the
experiment, half of the listeners were told that the talker was from
Detroit and the other half were told that the talker was from Canada.
Niedzielski (1999) found that the label she
provided about the talker's region of origin produced a significant
effect on the listeners' performance. In particular, the listeners in
the Detroit-label group consistently selected canonical, unshifted vowels
as the best match, whereas the listeners in the Canada-label group
selected vowel tokens that more closely matched the talker's actual
productions.
The results of Niedzielski's (1999)
study suggest that Northern listeners may not perceive the vowel shifts
that are present in their own speech. Similarly, in the present study, the
fact that the Non-Mobile Northern listener group perceived the Northern
and Midland talkers as being highly similar, despite robust
acoustic-phonetic differences between the two groups, suggests that
listeners who have lived only in the Northern dialect region may not
perceive the phonological differences between themselves and Midland
talkers.
On the other hand, participants who were not from the North and those
participants who had lived in multiple dialect regions perceived the
Northern and New England talkers as being more similar than the Northern
and Midland talkers. This perceived similarity is supported by the
acoustic analysis of the talkers described by Clopper et al. (2005), which revealed consistent
raising in the North and variable
raising in New England, and by other research suggesting that New England
may be the geographic origin of the Northern Cities Chain Shift, resulting
in some phonological similarities between New England and Northern talkers
(Boberg, 2001). Thus, the perceptual similarity
spaces of the Midland and Mobile Northern listener groups may more
accurately reflect the phonological similarities of the different regional
dialects than the Non-Mobile Northern listener group.
Response biases and asymmetries
The common aspects of the residential history of the listeners
influenced the response biases that were observed consistently across all
four listener groups. In particular, the negative bias towards responding
“New England” may be due to a general unfamiliarity with New
England speech. Of the Mobile listeners, only five out of 49 (10%) had
lived in New England for any period of time. The listeners who had not
lived in New England may have been particularly limited in their exposure
to New England speech due to the relatively small number of students at
Indiana University who come from the New England area. Table 6 shows the percentage of entering undergraduate
students in 2002 from each of the six dialect regions included in the
Nationwide Speech Project corpus. It is clear that even in a diverse
university setting like Bloomington, Indiana, participants may not have
encountered very many talkers from New England. This general unfamiliarity
with New England speech may be the factor that was responsible for the
strong negative bias for “New England” responses.
Percentage of 2002 Indiana University first-year students from each of
the six dialect regions included in the Nationwide Speech Project
corpus
Similarly, the positive bias for the Midland talkers may have been due
to the extreme familiarity of the listeners with talkers from this region.
Indiana University is located in the Midland dialect region and the
listeners in this study may have responded “Midland” more
often because that response was equivalent to “here” for our
listeners. In addition, the Midland dialect is also one of the
best-represented dialect regions at the University. Therefore, the
listeners may have adopted “Midland” as a default benchmark
response for all talkers who sounded like themselves, resulting in a large
positive bias for the “Midland” response.
Familiarity, or lack thereof, may also be related to the asymmetries
found in the stimulus-response confusion matrices. In particular, the fact
that Mid-Atlantic talkers were frequently identified as New Englanders but
New Englanders were most often misidentified as Midlanders is consistent
with the claim that the listeners in the current study were unfamiliar
with the New England dialect. In addition, these results also suggest that
the listeners recruited for participation in this study may have only a
single category for the Northeastern dialects, and that they expect all
talkers from the entire Northeastern region to sound like Mid-Atlantic
talkers. That is, the listeners do not know which phonological properties
are associated with New England talkers (the low-back merger and variable
raising) and which ones are unique to Mid-Atlantic talkers (F2 alignment
of
). An alternative interpretation is that the listeners were
simply not attending to the distinction between the two Northeastern
groups, like the Non-Mobile Northerners' apparent inattention to the
differences between Northern and Midland talkers. Future research should
examine the perceptual categorization performance of listeners from the
Mid-Atlantic and New England regions to determine whether this effect is
due to familiarity and exposure or to a general lack of attention to the
phonological differences between these two varieties.
CONCLUSIONS
Naïve listeners categorized the talkers from the NSP corpus by
regional dialect with 26% accuracy overall. The listeners in the present
study were all young adults who differed in their linguistic experience
and exposure to dialect variation on two specific dimensions: geographic
mobility and region of origin. While the residential history of the
listeners did not directly affect the accuracy of their performance in the
six-alternative forced-choice task, it did contribute to the patterns of
confusions made by the listeners. In particular, mobility increased the
distinctiveness of different varieties, presumably as a result of greater
experience with specific varieties and with language variation in general.
Frequency of exposure has been shown to play an important role in the
development of robust perceptual categories in the laboratory,
particularly when the participants' experience involves not only a
specific item, but also the appropriate category label for that item
(Barsalou, 1985). By living in several different
regions of the country, the mobile listeners had the opportunity to
develop more robust categories through greater exposure to talkers from
different dialect regions and implicit knowledge of the
appropriate category label for those talkers. Additional research is
needed to determine how much exposure to different dialects and at what
age is most beneficial for developing robust cognitive representations of
dialect variation.
Geographic location, on the other hand, was found to reduce the
distinctiveness of certain varieties due to commonly held social beliefs
or stereotypes. In the present study, the Non-Mobile Northerners perceived
the Northern and Midland talkers as being more similar to each other than
the other listeners did, presumably because they did not perceive the
differences between the two dialects and they believed that the two groups
were highly similar in their speech. In terms of categorization, this
finding suggests a “shrinking” of the perceptual distance
between the Northern and Midland talkers for the Non-Mobile Northern
listeners due to a lack of attention to the phonological differences
between the two dialects (see Nosofsky, 1986).
Additional research is needed to determine whether the perceptual
shrinking observed in studies of dialect classification is due to
misperception of the linguistic properties of the signal or perceptual
biases, such as those reported by Niedzielski (1999) in her vowel-matching task.
